Distance Decay in International Trade Patterns - a Meta-analysis

Trade costs remain an important barrier to international trade in today’s globalizing economy. Despite the popular discussion on the “death of distance”, distance is still an important source of trade costs and continues to have an irrevocable impact on the patterns of international trade. The literature identifies various factors that can explain the importance of geographical proximity for bilateral trade. First, transport costs and costs of timeliness increase with distance. Moreover, psychic distance increases as well. Because of cultural unfamiliarity and information costs, traders have less knowledge of distant markets. Empirical estimates of the distance effect in trade abound. The evidence indicates that distance still matters for trade. However, differences in estimated effects across the literature make generalizations about the distance effect and its development over time more difficult. This paper performs a meta-analysis of existing empirical studies of bilateral trade, in order to contribute to our understanding of distance decay in trade. Meta-analysis is a statistical analysis of a set of existing empirical results in a specific research area, in order to integrate the findings. It constitutes a quantitative survey of the literature that explicitly addresses the causes of cross-study variation in empirical outcomes. To perform the meta-analysis, a sample of gravity studies was constructed that is as representative as possible. For this purpose, a literature search has been conducted on the Internet, using the Econlit database. Using the search string “trade and/or distance, and gravity, in all fields”, a list of 214 applicable studies has been identified. From this list, 30 studies were randomly selected into the meta-analysis sample. The paper focuses on two key issues. First, it investigates cross-estimate variation in the distance effect according to differences in, e.g., time period concerned, data type used, or empirical specification and estimation method used. Then, we analyse whether the impact of distance has declined over time.

The internal market and the Dutch economy: implications for trade and economic growth

This paper estimates the effects of the formation and development of the Internal Market (IM) in the European Union on income per capita for the EU and specifically for the Netherlands, since its appearance in 1958. It does so in two stages. First, gravity equations are estimated to identify the impact of the IM on bilateral trade in goods and services and Foreign Direct Investment (FDI). The results of the first stage show that 8 percent of the exports and imports of goods by the EU members can be attributed to the IM. For services trade, the IM effects are somewhat smaller: about 5 percent of EU members' services trade. The IM has a bigger impact on FDI stocks. For the Netherlands, the IM has about twice as large an effect on trade in goods compared to the results for the EU. For services trade and FDI, the effects are in line with the results for the EU. Second, the trade-enhancing effect of IM on GDP is estimated. For 2005, IM integration of goods markets has yielded 2 to 3 percent higher per capita income in the EU, and about 4 to 6 percent higher income per capita in the Netherlands. If the current level of integration effects with respect to the IM for goods and services persists, GDP per capita in the long run will increase by about 10 percent in the EU and about 17 percent in the Netherlands.

The herd behavior index: A new measure for systemic risk in financial markets.

We introduce a new and easy to calculate measure for systemic risk in financial markets. This measure is baptized the Herd Behavior Index (HIX). It is model-independent and forward looking, based on observed option data. In order to determine the degree of systemic risk or herd behavior in a financial market one should compare the observed market situation with the extreme (theoretical) situation under which the whole system is driven by a single factor. The Herd Behavior Index (HIX) is defined as the ratio of an option-based estimate of the risk-neutral variance of the market index and an option-based estimate of the corresponding variance of this extreme market situation. Using the theory of comonotonicity, the extreme situation can easily be backed out of the observed option quotes. The HIX can be determined for any market index provided an appropriate series of vanilla options is traded on this index as well as on its components. As an illustration, we determine historical values of the 30-days implied Herd Behavior Index for the Dow Jones Industrial Average, covering the period January 2003 to October 2009.Comonotonicity; systemic risk; correlation; VIX volatility index;

On an optimization problem related to static super-replicating strategies

In this paper, we investigate an optimization problem related to super-replicating strategies for European-type call options written on a weighted sum of asset prices, following the initial approach in Chen et al. (2008). Three issues are investigated. The first issue is the (non-)uniqueness of the optimal solution. The second issue is the generalization to an optimization problem where the weights may be random. This theory is then applied to static super-replication strategies for some exotic options in a stochastic interest rate setting. The third issue is the study of the co-existence of the comonotonicity property and the martingale property.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Determinants of regional productivity growth in Europe: an empirical analysis

Discussion on the possibilities for and barriers to income convergence and catch-up growth is at the heart of the debate on European regional economic policy. This study presents an empirical analysis of the determinants of regional productivity growth in Europe, using the most recent Cambridge Econometrics regional database, EU KLEMS growth and productivity accounts and EuroStat R&D data. We apply a reduced-form empirical specification for semi-endogenous productivity growth that allows for differences in steady state income levels and long-run growth rates. Productivity growth in a region depends on its level of human capital, the investments in R&D, and the productivity gap with the technology frontier. Empirical findings show that these factors are interrelated. Apart from a technology gap, absorptive capacity is important to realize catch-up. Both convergence and divergence of productivity across regions are possible. Results show that all considered factors have significant effect on disparity in regional productivity growth, although effects across manufacturing and service sectors are different. The estimated model also features stable dynamic properties in response to an exogenous shock. Keywords: Semi-endogenous Growth, Regional Convergence, International Transfer of Technology, human capital, R&D.

FIX - The fear index. Measuring market fear.

In this paper, we propose a new fear index based on (equity) option surfaces of an index and its components. The quanti¯cation of the fear level will be solely based on option price data. The index takes into account market risk via the VIX volatility barometer, liquidity risk via the concept of implied liquidity, and systemic risk and herd-behavior via the concept of comonotonicity. It thus allows us to measure an overall level of fear (excluding credit risk) in the market as well as to identify precisely the individual importance of the distinct risk components (market, liquidity or systemic risk). As a side result we also derive an upperbound for the VIX.

Совершенствование инновационной деятельности предприятия (на примере ОАО «Промсвязь»)

A characterisation theorem for best uniform wavenumber approximations by central difference schemes is presented. A central difference stencil is derived based on the theorem and is compared with dispersion relation preserving schemes and with classical central differences for a relevant test problem

The Space of Gravity: Spatial Filtering Estimation of a Gravity Model for Bilateral Trade

Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of emerging literature, and shows that spatial filtering (SF) techniques can take into account the autocorrelation in trade flows. Furthermore, we show that the use of origin and destination specific spatial filters goes a long way in correcting for omitted variable bias in an otherwise standard empirical gravity equation. For a cross-section of bilateral trade flows, we compare an SF approach to two benchmark specifications that are consistent with theoretically derived gravity. The results are relevant for a number of reasons. First, we correct for autocorrelation in the residuals. Second, we suggest that the empirical gravity equation can still be considered in applied work, despite the theoretical arguments for its misspecification due to omitted multilateral resistance terms. Third, if we include SF variables, we can still resort to any desired estimator, such as OLS, Poisson or negative binomial regression. Finally, interpreting endogeneity bias as autocorrelation in regressor variables and residuals allows for a more general specification of the gravity equation than the relatively restricted theoretical gravity equation. In particular, we can include additional country-specific push and pull variables, besides GDP (e.g., land area, landlockedness, and per capita GDP). A final analysis provides autocorrelation diagnostics according to different candidate indicators